180 citations · 181 across the 13 of their papers we have counts for
13 papers
Conformalized Large Language Models under Configuration Shift
Yuqicheng Zhu, Jialin Yu, Lin Li +7
Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs), providing prediction sets…
AWM: Answerable Working Memory for Long-Document VQA Agents
Dongzhuoran Zhou, Yuqicheng Zhu, Yule Liu +5
Long-document visual question answering increasingly relies on VLM agents that retrieve candidate pages, inspect page images, write findings to working memory, and synthesize answe…
MV-Bench: Benchmarking Multimodal Large Language Models for Coordinated Multi-View Interface Construction
Yue Zhao, Hongxu Liu, Feiyu Wang +5
Multimodal large language models (MLLMs) are increasingly expected to automate visualization development by generating code directly from visual designs. However, existing evaluati…
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
V Team, Wenyi Hong, Xiaotao Gu +94
We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…
Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification
Zehai He, Wenyi Hong, Zhen Yang +4
Recent advances in large language models have improved the capabilities of coding agents, yet systematic evaluation of complex, end-to-end website development remains limited. To a…
PlotGen-Bench: Evaluating VLMs on Generating Visualization Code from Diverse Plots across Multiple Libraries
Yi Zhao, Zhen Yang, Shuaiqi Duan +4
Recent advances in vision-language models (VLMs) have expanded their multimodal code generation capabilities, yet their ability to generate executable visualization code from plots…
WebVIA: A Web-based Vision-Language Agentic Framework for Interactive and Verifiable UI-to-Code Generation
Mingde Xu, Zhen Yang, Wenyi Hong +6
User interface (UI) development requires translating design mockups into functional code, a process that remains repetitive and labor-intensive. While recent Vision-Language Models…
UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization
Zhen Yang, Wenyi Hong, Mingde Xu +5
UI-to-code aims to translate UI screenshots into executable front-end code. Despite progress with vision-language models (VLMs), most existing methods formulate UI-to-code as a sin…
VisScience: An Extensive Benchmark for Evaluating K12 Educational Multi-modal Scientific Reasoning
Zhihuan Jiang, Zhen Yang, Jinhao Chen +4
Multi-modal large language models (MLLMs) have demonstrated promising capabilities across various tasks by integrating textual and visual information to achieve visual understandin…
MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model
Zhen Yang, Jinhao Chen, Zhengxiao Du +6
Large language models (LLMs) have demonstrated significant capabilities in mathematical reasoning, particularly with text-based mathematical problems. However, current multi-modal…
ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
Team GLM, :, Aohan Zeng +56
We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes…
Does Negative Sampling Matter? A Review with Insights into its Theory and Applications
Zhen Yang, Ming Ding, Tinglin Huang +5
Negative sampling has swiftly risen to prominence as a focal point of research, with wide-ranging applications spanning machine learning, computer vision, natural language processi…
TriSampler: A Better Negative Sampling Principle for Dense Retrieval
Zhen Yang, Zhou Shao, Yuxiao Dong +1
Negative sampling stands as a pivotal technique in dense retrieval, essential for training effective retrieval models and significantly impacting retrieval performance. While exist…